Model Coupling - Revision history

Arango: /* Earth System Modeling Framework (ESMF) */

2022-05-04T00:51:11Z

Earth System Modeling Framework (ESMF)

← Older revision		Revision as of 00:51, 4 May 2022
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	A prototype of the ROMS coupling framework based on the '''ESMF/NUOPC''' library is illustrated in Figure 1 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the '''ESM''' components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a '''NUOP'''C <span class="red">cap</span> file interface. The Connectors between '''ESM''' components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the ~~Data~~ Model since the grids are incongruent. The ~~Data~~ Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.		A prototype of the ROMS coupling framework based on the '''ESMF/NUOPC''' library is illustrated in Figure 1 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the '''ESM''' components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a '''NUOP'''C <span class="red">cap</span> file interface. The Connectors between '''ESM''' components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the '''DATA''' Model since the grids are incongruent. The '''DATA''' Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.

	===Sequential Vs. Concurrent Mode===		===Sequential Vs. Concurrent Mode===

Arango: /* Earth System Modeling Framework (ESMF) */

2022-05-04T00:49:44Z

Earth System Modeling Framework (ESMF)

← Older revision		Revision as of 00:49, 4 May 2022
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	The critical Fortran module that sits on top of each '''ESM''' is the so-called '''NUOPC''' <span class="red">cap</span> file. There is a separate <span class="red">cap</span> file for each coupled component, which, from the ROMS perspective, corresponds to the atmosphere, sea-ice, wave model, etc. Therefore, it is an abstract block that allows ROMS to communicate and exchange data seamlessly within the '''ESMF/NUOPC''' framework. The ROMS and other '''ESM''' grids may (and usually do) have a different geographical extent and horizontal resolution. So if, for example, the atmosphere component domain is larger than the ROMS domain, it is necessary to provide data from another source to the atmosphere model at all of the surface grid points that lie outside the ROMS domain. Therefore, a DATA component and its <span class="red">cap</span> file is also required for most applications. In this case, SST is exported from ROMS and '''DATA''' to the atmosphere component which imports a melded SST field.		The critical Fortran module that sits on top of each '''ESM''' is the so-called '''NUOPC''' <span class="red">cap</span> file. There is a separate <span class="red">cap</span> file for each coupled component, which, from the ROMS perspective, corresponds to the atmosphere, sea-ice, wave model, etc. Therefore, it is an abstract block that allows ROMS to communicate and exchange data seamlessly within the '''ESMF/NUOPC''' framework. The ROMS and other '''ESM''' grids may (and usually do) have a different geographical extent and horizontal resolution. So if, for example, the atmosphere component domain is larger than the ROMS domain, it is necessary to provide data from another source to the atmosphere model at all of the surface grid points that lie outside the ROMS domain. Therefore, a DATA component and its <span class="red">cap</span> file is also required for most applications. In this case, SST is exported from ROMS and '''DATA''' to the atmosphere component which imports a melded SST field.

	The ROMS coupling interface with the '''ESMF/NUOPC''' library allows both driver and component methods of operation. In the driver method, it provides all the interfaces needed to couple to other ESM components including the executable driver, NUOPC-based generic '''ESM''' component services, model gridded components or NUOPC Model cap files, connectors between components for re-gridding source and destination fields, input scripts, and coupling metadata management. A NUOPC Model cap is a Fortran code layer that sits on top of the ESM component, making calls to the numerical kernel via the '''initialize''', '''run''', and '''finalize''' phases. Alternatively, in the component method, the [[NUOPC_Cap_UFS\|stand-alone]] ROMS '''NUOPC''' <span class="red">cap</span> module is also provided, and it can be adapted and incorporated into other NUOPC-based coupling systems, like the NOAA Environmental Modeling System ('''NEMS''') or the Community Mediator for Earth Prediction Systems ('''CMEPS''').		The ROMS coupling interface with the '''ESMF/NUOPC''' library allows both driver and component methods of operation. In the driver method, it provides all the interfaces needed to couple to other '''ESM''' components including the executable driver, NUOPC-based generic '''ESM''' component services, model gridded components or NUOPC Model cap files, connectors between components for re-gridding source and destination fields, input scripts, and coupling metadata management. A NUOPC Model cap is a Fortran code layer that sits on top of the '''ESM''' component, making calls to the numerical kernel via the '''initialize''', '''run''', and '''finalize''' phases. Alternatively, in the component method, the [[NUOPC_Cap_UFS\|stand-alone]] ROMS '''NUOPC''' <span class="red">cap</span> module is also provided, and it can be adapted and incorporated into other '''NUOPC'''-based coupling systems, like the '''NOAA''' Environmental Modeling System ('''NEMS''') or the Community Mediator for Earth Prediction Systems ('''CMEPS''').

	[[Image:ROMS_Coupling.png\|800px\|center]]		[[Image:ROMS_Coupling.png\|800px\|center]]

	<center>'''''Figure 1:''''' ROMS driver mode ESMF/NUOPC coupling framework</center>		<center>'''''Figure 1:''''' ROMS driver mode '''ESMF/NUOPC''' coupling framework</center>


	A prototype of the ROMS coupling framework based on the '''ESMF/NUOPC''' library is illustrated in Figure 1 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the '''ESM''' components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a ~~NUOPC~~ cap file interface. The Connectors between ESM components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the Data Model since the grids are incongruent. The Data Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.		A prototype of the ROMS coupling framework based on the '''ESMF/NUOPC''' library is illustrated in Figure 1 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the '''ESM''' components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a '''NUOP'''C <span class="red">cap</span> file interface. The Connectors between '''ESM''' components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the Data Model since the grids are incongruent. The Data Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.

	===Sequential Vs. Concurrent Mode===		===Sequential Vs. Concurrent Mode===

Arango: /* Introduction */

2022-05-04T00:47:32Z

Introduction

← Older revision		Revision as of 00:47, 4 May 2022
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	==Introduction==		==Introduction==
	The coupling of atmosphere and ocean plays an essential role in the Earth climate and the long- and short-term predictability of both systems. Typical uncoupled ocean modeling systems utilize atmospheric model data snapshots from files at coarser temporal and spatial resolutions and interpolate the forcing fields at each time-step to drive circulation forward. Similarly, some atmospheric modeling systems have simplistic representations of oceanic and air-sea transfer processes. They may use a static sea surface temperature field derived from satellite imagery composited over days to weeks, or one-dimensional ocean mixing models that do not represent three-dimensional baroclinic circulation on continental shelves. This method performs well in regions where the ocean evolves slowly relative to the atmosphere and where the sea state has limited impact on the atmospheric state. However, in coastal areas, the ocean can respond to the atmosphere rapidly and is highly variable over short spatial scales. In these cases, significant feedbacks between the ocean and atmosphere occur regularly.		The coupling of atmosphere and ocean plays an essential role in the Earth's climate and the long- and short-term predictability of both systems. Typical uncoupled ocean modeling systems utilize atmospheric model data snapshots from files at coarser temporal and spatial resolutions and interpolate the forcing fields at each time step to drive circulation forward. Similarly, some atmospheric modeling systems have simplistic representations of oceanic and air-sea transfer processes. They may use a static sea surface temperature field derived from satellite imagery composited over days to weeks, or one-dimensional ocean mixing models that do not represent three-dimensional baroclinic circulation on continental shelves. This method performs well in regions where the ocean evolves slowly relative to the atmosphere and where the sea state has a limited impact on the atmospheric state. However, in coastal areas, the ocean can respond to the atmosphere rapidly and is highly variable over short spatial scales. In these cases, significant feedbacks between the ocean and atmosphere occur regularly.

	Several coupling interfaces exist to exchange data between ESM components including the ESMF (Collins et al., 2005), MCT (Larson et al., 2005), and OASIS (Valcke, 2013) libraries. All three coupling libraries have been used for coupling ROMS with an atmosphere model (e.g., Turuncoglu and Sannino, 2017, Warner et al., 2010, Renault et al., 2016, respectively).		Several coupling interfaces exist to exchange data between '''ESM''' components including the '''ESMF''' (Collins et al., 2005), '''MCT''' (Larson et al., 2005), and '''OASIS''' (Valcke, 2013) libraries. All three coupling libraries have been used for coupling ROMS with an atmosphere model (e.g., Turuncoglu and Sannino, 2017, Warner et al., 2010, Renault et al., 2016, respectively).

	==Earth System Modeling Framework (ESMF)==		==Earth System Modeling Framework (ESMF)==

Arango: /* Regridding and Extrapolation Methods */

2022-05-04T00:45:50Z

Regridding and Extrapolation Methods

← Older revision		Revision as of 00:45, 4 May 2022
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	===Regridding and Extrapolation Methods===		===Regridding and Extrapolation Methods===
	Regridding interpolation methods between source and destination fields can be <span class="red">bilinear</span> or <span class="red">conservative</span>. Unmapped cells during regridding are usually located at land/sea boundaries. These unmapped cells can be mapped using the following methods: <span class="blue">nearest source to destination</span>, <span class="blue">nearest inverse distance average</span>, <span class="blue">creep fill at specified level</span>, or <span class="blue">two steps extrapolation</span> (Turuncoglu).		Regridding interpolation methods between source and destination fields can be <span class="red">bilinear</span> or <span class="red">conservative</span>. Unmapped cells during regridding are usually located at land/sea boundaries. These unmapped cells can be mapped using the following methods: <span class="blue">nearest source to destination</span>, <span class="blue">nearest inverse distance average</span>, <span class="blue">creep fill at specified level</span>, or <span class="blue">two steps extrapolation</span> (Turuncoglu).

	~~<span class="blue">Indian Ocean Land/Sea Masks Mismatch??</span>~~

	<div class="box"><span class="twilightBlue"># <span class="violet">regrid_method</span> Field regridding method from source to destination:<br /># bilinear => bilinear interpolation<br /># patch => high-order patch recovery<br /># conservative1 => first-order conservative<br /># conservative2 => second-order conservative<br /># nearest => nearest neighbor interpolation<br /># <span class="violet">extrapolate_method</span> Field extrapolation method for unmapped points:<br /># none => no extrapolation<br /># nearest => nearest source to destination<br /># idavg => nearest inverse distance average<br /># creep => creep fill at specified level<br /># 2steps => Turuncoglu's 2 steps extrapolation<br />#<br /># The ESM imported fields are processed as:<br />#<br /># field (destination_units) = field (source_units) * scale + add_offset</span><br /><br /><span class="violet">ATM_component</span>: <span class="green">&ATM</span> <span class="twilightBlue">WRF</span><br /><br /><span class="violet">DATA_component</span>: <span class="twilightBlue">data.nc</span><br /><br /><span class="violet">ROMS_component</span>: <span class="green">&OCN</span> <span class="twilightBlue">ROMS</span><br /><br /><span class="violet">metadata</span>:<br /><br /> - <span class="violet">standard_name</span>: <span class="twilightBlue">sea_surface_temperature</span><br /> <span class="violet">long_name</span>: <span class="twilightBlue">sea surface potential temperature</span><br /> <span class="violet">short_name</span>: <span class="twilightBlue">SST</span><br /> <span class="violet">data_variables</span>: <span class="red">[<span class="twilightBlue">temperature</span>, <span class="twilightBlue">time</span>]</span><br /> <span class="violet">source_units</span>: <span class="twilightBlue">C</span><br /> <span class="violet">destination_units</span>: <span class="twilightBlue">K</span><br /> <span class="violet">source_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">destination_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">add_offset</span>: <span class="twilightBlue">273.15d0</span><br /> <span class="violet">scale</span>: <span class="twilightBlue">1.0d0</span><br /> <span class="violet">debug_write</span>: <span class="twilightBlue">false</span><br /> <span class="violet">connected_to</span>: <span class="salmon">ATM</span><br /> <span class="violet">regrid_method</span>: <span class="twilightBlue">bilinear</span><br /> <span class="violet">extrapolate_method</span>: <span class="twilightBlue">nearest</span><br /><br /> - <span class="violet">standard_name</span>: <span class="twilightBlue">sea_surface_temperature_data</span><br /> <span class="violet">long_name</span>: <span class="twilightBlue">sea surface temperature data</span><br /> <span class="violet">short_name</span>: <span class="twilightBlue">dSST</span><br /> <span class="violet">data_variables</span>: <span class="red">[<span class="twilightBlue">temperature</span>, <span class="twilightBlue">time</span>]</span><br /> <span class="violet">source_units</span>: <span class="twilightBlue">C</span><br /> <span class="violet">destination_units</span>: <span class="twilightBlue">K</span><br /> <span class="violet">source_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">destination_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">add_offset</span>: <span class="twilightBlue">273.15d0</span><br /> <span class="violet">scale</span>: <span class="twilightBlue">1.0d0</span><br /> <span class="violet">debug_write</span>: <span class="twilightBlue">false</span><br /> <span class="violet">connected_to</span>: <span class="salmon">ATM</span><br /> <span class="violet">regrid_method</span>: <span class="twilightBlue">bilinear</span><br /> <span class="violet">extrapolate_method</span>: <span class="twilightBlue">nearest</span></div>		<div class="box"><span class="twilightBlue"># <span class="violet">regrid_method</span> Field regridding method from source to destination:<br /># bilinear => bilinear interpolation<br /># patch => high-order patch recovery<br /># conservative1 => first-order conservative<br /># conservative2 => second-order conservative<br /># nearest => nearest neighbor interpolation<br /># <span class="violet">extrapolate_method</span> Field extrapolation method for unmapped points:<br /># none => no extrapolation<br /># nearest => nearest source to destination<br /># idavg => nearest inverse distance average<br /># creep => creep fill at specified level<br /># 2steps => Turuncoglu's 2 steps extrapolation<br />#<br /># The ESM imported fields are processed as:<br />#<br /># field (destination_units) = field (source_units) * scale + add_offset</span><br /><br /><span class="violet">ATM_component</span>: <span class="green">&ATM</span> <span class="twilightBlue">WRF</span><br /><br /><span class="violet">DATA_component</span>: <span class="twilightBlue">data.nc</span><br /><br /><span class="violet">ROMS_component</span>: <span class="green">&OCN</span> <span class="twilightBlue">ROMS</span><br /><br /><span class="violet">metadata</span>:<br /><br /> - <span class="violet">standard_name</span>: <span class="twilightBlue">sea_surface_temperature</span><br /> <span class="violet">long_name</span>: <span class="twilightBlue">sea surface potential temperature</span><br /> <span class="violet">short_name</span>: <span class="twilightBlue">SST</span><br /> <span class="violet">data_variables</span>: <span class="red">[<span class="twilightBlue">temperature</span>, <span class="twilightBlue">time</span>]</span><br /> <span class="violet">source_units</span>: <span class="twilightBlue">C</span><br /> <span class="violet">destination_units</span>: <span class="twilightBlue">K</span><br /> <span class="violet">source_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">destination_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">add_offset</span>: <span class="twilightBlue">273.15d0</span><br /> <span class="violet">scale</span>: <span class="twilightBlue">1.0d0</span><br /> <span class="violet">debug_write</span>: <span class="twilightBlue">false</span><br /> <span class="violet">connected_to</span>: <span class="salmon">ATM</span><br /> <span class="violet">regrid_method</span>: <span class="twilightBlue">bilinear</span><br /> <span class="violet">extrapolate_method</span>: <span class="twilightBlue">nearest</span><br /><br /> - <span class="violet">standard_name</span>: <span class="twilightBlue">sea_surface_temperature_data</span><br /> <span class="violet">long_name</span>: <span class="twilightBlue">sea surface temperature data</span><br /> <span class="violet">short_name</span>: <span class="twilightBlue">dSST</span><br /> <span class="violet">data_variables</span>: <span class="red">[<span class="twilightBlue">temperature</span>, <span class="twilightBlue">time</span>]</span><br /> <span class="violet">source_units</span>: <span class="twilightBlue">C</span><br /> <span class="violet">destination_units</span>: <span class="twilightBlue">K</span><br /> <span class="violet">source_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">destination_grid</span>: <span class="twilightBlue">cell_center</span><br /> <span class="violet">add_offset</span>: <span class="twilightBlue">273.15d0</span><br /> <span class="violet">scale</span>: <span class="twilightBlue">1.0d0</span><br /> <span class="violet">debug_write</span>: <span class="twilightBlue">false</span><br /> <span class="violet">connected_to</span>: <span class="salmon">ATM</span><br /> <span class="violet">regrid_method</span>: <span class="twilightBlue">bilinear</span><br /> <span class="violet">extrapolate_method</span>: <span class="twilightBlue">nearest</span></div>

Arango: /* Earth System Modeling Framework (ESMF) */

2022-05-04T00:44:42Z

Earth System Modeling Framework (ESMF)

← Older revision		Revision as of 00:44, 4 May 2022
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	==Earth System Modeling Framework (ESMF)==		==Earth System Modeling Framework (ESMF)==
	Significant progress has been made over the past decade in the standardization of coupling tools without reducing model diversity through the Earth System Modeling Framework (ESMF; Collins ''et al.'', 2005) and the National Unified Operational Prediction Capability (NUOPC) consortia. The NUOPC layer is a simplified infrastructure on top of the ESMF library (version 7 or higher) that provides conventions and templates to facilitate easy coupling between Earth System Models (ESM). It consists of four components: (i) a driver, (ii) the models, (iii) mediators, and (iv) connectors. The driver controls the models, mediators, connectors, and coordinates tasks such as initialization and time stepping. The mediators are custom codes that facilitate the coupling of the models, and control tasks such as flux calculations, rescaling, and averaging. The connectors join ESM components and perform operations such as regridding between the source and destination fields when needed. While the NUOPC layer is available in ESMF version 7 of higher, ROMS coupling '''requires version 8 or higher''' because it uses the RunSequence input configuration script and uses version 8 features for nesting.		Significant progress has been made over the past decade in the standardization of coupling tools without reducing model diversity through the Earth System Modeling Framework ('''ESMF'''; Collins ''et al.'', 2005) and the National Unified Operational Prediction Capability ('''NUOPC''') consortia. The '''NUOPC''' layer is a simplified infrastructure on top of the '''ESMF''' library (version 7 or higher) that provides conventions and templates to facilitate easy coupling between Earth System Models ('''ESM'''). It consists of four components: (i) a driver, (ii) the models, (iii) mediators, and (iv) connectors. The driver controls the models, mediators, connectors, and coordinates tasks such as initialization and time stepping. The mediators are custom codes that facilitate the coupling of the models, and control tasks such as flux calculations, rescaling, and averaging. The connectors join '''ESM''' components and perform operations such as regridding between the source and destination fields when needed. While the '''NUOPC''' layer is available in '''ESMF''' version '''7''' of higher, ROMS coupling '''requires version 8 or higher''' because it uses the '''RunSequence''' input configuration script and uses version '''8''' features for nesting.

	The critical Fortran module that sits on top of each ESM is the so-called NUOPC <span class="red">cap</span> file. There is a separate <span class="red">cap</span> file for each coupled component, which, from the ROMS perspective, corresponds to the atmosphere, sea-ice, wave model, etc. Therefore, it is an abstract block that allows ROMS to communicate and exchange data seamlessly within the ESMF/NUOPC framework. The ROMS and other ESM grids may (and usually do) have a different geographical extent and horizontal resolution. So if, for example, the atmosphere component domain is larger than the ROMS domain, it is necessary to provide data from another source to the atmosphere model at all of the surface grid-points that lie outside the ROMS domain. Therefore, a DATA component and its <span class="red">cap</span> file is also required for most applications. In this case, SST is exported from ROMS and DATA to the atmosphere component which imports a melded SST field.		The critical Fortran module that sits on top of each '''ESM''' is the so-called '''NUOPC''' <span class="red">cap</span> file. There is a separate <span class="red">cap</span> file for each coupled component, which, from the ROMS perspective, corresponds to the atmosphere, sea-ice, wave model, etc. Therefore, it is an abstract block that allows ROMS to communicate and exchange data seamlessly within the '''ESMF/NUOPC''' framework. The ROMS and other '''ESM''' grids may (and usually do) have a different geographical extent and horizontal resolution. So if, for example, the atmosphere component domain is larger than the ROMS domain, it is necessary to provide data from another source to the atmosphere model at all of the surface grid points that lie outside the ROMS domain. Therefore, a DATA component and its <span class="red">cap</span> file is also required for most applications. In this case, SST is exported from ROMS and '''DATA''' to the atmosphere component which imports a melded SST field.

	The ROMS coupling interface with the ESMF/NUOPC library allows both driver and component methods of operation. In the driver method, it provides all the interfaces needed to couple to other ESM components including the executable driver, NUOPC-based generic ESM component services, model gridded components or NUOPC Model cap files, connectors between components for re-gridding source and destination fields, input scripts, and coupling metadata management. A NUOPC Model cap is a Fortran code layer that sits on top of the ESM component, making calls to the numerical kernel via the initialize, run, and finalize phases. Alternatively, in the component method, the NUOPC ~~ROMS~~ cap module is provided, and it can be adapted and incorporated into other NUOPC-based coupling systems, like the NOAA Environmental Modeling System (NEMS).		The ROMS coupling interface with the '''ESMF/NUOPC''' library allows both driver and component methods of operation. In the driver method, it provides all the interfaces needed to couple to other ESM components including the executable driver, NUOPC-based generic '''ESM''' component services, model gridded components or NUOPC Model cap files, connectors between components for re-gridding source and destination fields, input scripts, and coupling metadata management. A NUOPC Model cap is a Fortran code layer that sits on top of the ESM component, making calls to the numerical kernel via the '''initialize''', '''run''', and '''finalize''' phases. Alternatively, in the component method, the [[NUOPC_Cap_UFS\|stand-alone]] ROMS '''NUOPC''' <span class="red">cap</span> module is also provided, and it can be adapted and incorporated into other NUOPC-based coupling systems, like the NOAA Environmental Modeling System ('''NEMS''') or the Community Mediator for Earth Prediction Systems ('''CMEPS''').

	[[Image:ROMS_Coupling.png\|800px\|center]]		[[Image:ROMS_Coupling.png\|800px\|center]]
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	A prototype of the ROMS coupling framework based on the ESMF/NUOPC library is illustrated in Figure 2 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the ESM components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a NUOPC cap file interface. The Connectors between ESM components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the Data Model since the grids are incongruent. The Data Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.		A prototype of the ROMS coupling framework based on the '''ESMF/NUOPC''' library is illustrated in Figure 1 showing the Driver, Models, and Connectors. The Driver controls all the aspects of the coupling between the '''ESM''' components and their connections: configuration, initialization, time-stepping sequence, data exchanges, and termination. The Models are the gridded data and gridded geophysical numerical kernels wrapped into a NUOPC cap file interface. The Connectors between ESM components execute the remapping and regridding between the source and destination fields. The interpolation is usually linear with extrapolation support in the vicinity of masked grid cells. In the example below, the coupling framework will include an Atmosphere Model, the Ocean Model (ROMS), and the Data Model since the grids are incongruent. The Data Model is needed because the Atmosphere Model requires sea surface temperature (SST) on those grid points not covered by ROMS.

	===Sequential Vs. Concurrent Mode===		===Sequential Vs. Concurrent Mode===
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	* Set which ESM components are connected to the atmosphere component during coupling. If the atmosphere component has nested grids, indicate which grids are connected to the other ESM components, [1:[[Variables#NgridsA\|NgridsA]]] expected.<div class="box"> [[Variables#Coupled\|Coupled(OCN2ATM)]] == F T ! ROMS -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(ICE2ATM)]] == F ! seaice -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(WAV2ATM)]] == F ! wave -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(DAT2ATM)]] == T T ! DATA -> atmosphere connected</div>		* Set which ESM components are connected to the atmosphere component during coupling. If the atmosphere component has nested grids, indicate which grids are connected to the other ESM components, [1:[[Variables#NgridsA\|NgridsA]]] expected.<div class="box"> [[Variables#Coupled\|Coupled(OCN2ATM)]] == F T ! ROMS -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(ICE2ATM)]] == F ! seaice -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(WAV2ATM)]] == F ! wave -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(DAT2ATM)]] == T T ! DATA -> atmosphere connected</div>


	==Model Coupling Toolkit (MCT)==		==Model Coupling Toolkit (MCT)==

Robertson at 18:21, 27 April 2022

2022-04-27T18:21:58Z

← Older revision		Revision as of 18:21, 27 April 2022
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	* Set which ESM components are connected to the atmosphere component during coupling. If the atmosphere component has nested grids, indicate which grids are connected to the other ESM components, [1:[[Variables#NgridsA\|NgridsA]]] expected.<div class="box"> [[Variables#Coupled\|Coupled(OCN2ATM)]] == F T ! ROMS -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(ICE2ATM)]] == F ! seaice -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(WAV2ATM)]] == F ! wave -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(DAT2ATM)]] == T T ! DATA -> atmosphere connected</div>		* Set which ESM components are connected to the atmosphere component during coupling. If the atmosphere component has nested grids, indicate which grids are connected to the other ESM components, [1:[[Variables#NgridsA\|NgridsA]]] expected.<div class="box"> [[Variables#Coupled\|Coupled(OCN2ATM)]] == F T ! ROMS -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(ICE2ATM)]] == F ! seaice -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(WAV2ATM)]] == F ! wave -> atmosphere connected<br /> [[Variables#Coupled\|Coupled(DAT2ATM)]] == T T ! DATA -> atmosphere connected</div>


			==Model Coupling Toolkit (MCT)==
			The ROMS modeling system has been coupled to other fully developed models to provide increased modeling capabilites. For the coupling communications, we are using the Model Coupling Toolkit (http://www-unix.mcs.anl.gov/mct/). The original coupling is described in Warner, J.C., Perlin, N., and Skyllingstad, E.D. (2008). Using the Model Coupling Toolkit to couple earth system models, Environmental Modelling & Software, 23, 1240-1249. Since that publication, the coding has been modified to be more generic and allow interfaces to other couplers (such as ESMF).

			The coupling provides a mechanism for data transfer between models while they are running concurrently (at the same time). The model coupling requires that each model still needs its own grid, input parameters file, its own time step, forcing files (information not acquired from the other model), and each model writes its own output in its own format (just as if it was not coupled) on its own time interval. However the models are compiled into one executable and exchange information at user defined synchronization intervals.

			The current release of ROMS includes 2-way coupling to the wave model SWAN. For coupling to SWAN, the transferred fields are:

			Fields acquired from the WAVE Model: !
			!
			* Dwave Wave direction. !
			* Hwave Wave height. !
			* Lwave Wave length. !
			* Pwave_bot Wave bottom period. !
			* Pwave_top Wave surface period. !
			* Wave_break Percent of breakig waves. !
			* Wave_dissip Wave energy dissipation. !
			!
			Fields sent to the WAVE Model: !
			!
			* ubar Depth integrated xi-direction velocity. !
			* vbar Depth integrated eta-direction velocity. !
			* zeta Water surface elevation. !
			* h Bottom elevation. !


			For coupling to the Atmospheric Model WRF, (currently being tested, to be released in the future), the transferred fields are:

			Fields sent to the OCEAN Model: !
			!
			* PSFC Surface atmospheric pressure (mb) !
			* RELH Surface air relative humidity (-) !
			* T2 Surface 2m air temperature (degC) !
			* U10 U-Wind speed at 10 m (m/s) !
			* V10 V-Wind speed at 10 m (m/s) !
			* CLDFRA Cloud fraction (percent/100, so 0-1) !
			* RAIN Precipitation (kg/m2/s) !
			* SWDOWN Short wave radiation (Celsius m/s) !
			* GLW Long wave raditaion (Celsius m/s) !
			* USTRESS Surface u-stress (m2/s2) !
			* VSTRESS Surface v-stress (m2/s2) !

			Fields acquired from the OCEAN Model: !
			!
			* SST Sea surface temperature (degC) !

			The coupling must be compiled with MPI.
			Users need to first compile the Model Coupling Toolkit, as this library is linked to during the compilation. Examples of coupled applications distributed with the source code include the Tidal Inlet Test Case and the Tidal Headland Test case.

			Users need to modify the coupling*.in file to ensure that the correct fields are being transferred. Users should also read the information for the swan.in file.

Robertson at 18:20, 27 April 2022

2022-04-27T18:20:13Z

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Robertson at 17:20, 27 April 2022

2022-04-27T17:20:44Z

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Robertson at 18:33, 1 March 2022

2022-03-01T18:33:04Z

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	<div class="title">Model Coupling</div>__NOTOC__		<div class="title">Model Coupling</div>__NOTOC__

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Arango at 22:48, 20 February 2019

2019-02-20T22:48:11Z

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	==Introduction==		==Introduction==
	The coupling of atmosphere and ocean plays an essential role in the Earth climate and the long- and short-term predictability of both systems. Typical uncoupled ocean modeling systems utilize atmospheric model data snapshots from files at coarser temporal and spatial resolutions and interpolate the forcing fields at each time-step to drive circulation forward. Similarly, some atmospheric modeling systems have simplistic representations of oceanic and air-sea transfer processes. They may use a static sea surface temperature field derived from satellite imagery composited over days to weeks, or one-dimensional ocean mixing models that do not represent three-dimensional baroclinic circulation on continental shelves. This method performs well in regions where the ocean evolves slowly relative to the atmosphere and where the sea state has limited impact on the atmospheric state. However, in coastal areas, the ocean can respond to the atmosphere rapidly and is highly variable over short spatial scales. In these cases, significant feedbacks between the ocean and atmosphere occur regularly ~~(Olabarrieta et al., 2012; Glenn et al., 2016; Seroka et al., 2016, 2017; Chambers et al., 2014)~~.		The coupling of atmosphere and ocean plays an essential role in the Earth climate and the long- and short-term predictability of both systems. Typical uncoupled ocean modeling systems utilize atmospheric model data snapshots from files at coarser temporal and spatial resolutions and interpolate the forcing fields at each time-step to drive circulation forward. Similarly, some atmospheric modeling systems have simplistic representations of oceanic and air-sea transfer processes. They may use a static sea surface temperature field derived from satellite imagery composited over days to weeks, or one-dimensional ocean mixing models that do not represent three-dimensional baroclinic circulation on continental shelves. This method performs well in regions where the ocean evolves slowly relative to the atmosphere and where the sea state has limited impact on the atmospheric state. However, in coastal areas, the ocean can respond to the atmosphere rapidly and is highly variable over short spatial scales. In these cases, significant feedbacks between the ocean and atmosphere occur regularly.

	Several coupling interfaces exist to exchange data between ESM components including the ESMF (Collins et al., 2005), MCT (Larson et al., 2005), and OASIS (Valcke, 2013) libraries. All three coupling libraries have been used for coupling ROMS with an atmosphere model (e.g., Turuncoglu and Sannino, 2017, Warner et al., 2010, Renault et al., 2016, respectively).		Several coupling interfaces exist to exchange data between ESM components including the ESMF (Collins et al., 2005), MCT (Larson et al., 2005), and OASIS (Valcke, 2013) libraries. All three coupling libraries have been used for coupling ROMS with an atmosphere model (e.g., Turuncoglu and Sannino, 2017, Warner et al., 2010, Renault et al., 2016, respectively).